Detecting primordial features with LISA

Autor: Fumagalli, Jacopo, Pieroni, Mauro, Renaux-Petel, Sébastien, Witkowski, Lukas T.
Přispěvatelé: Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Cosmology and Astroparticle Physics
Popis: Oscillations in the frequency profile of the stochastic gravitational wave background are a characteristic prediction of small-scale features during inflation. In this paper we present a first investigation of the detection prospects of such oscillations with the upcoming space-based gravitational wave observatory LISA. As a proof of principle, we show for a selection of feature signals that the oscillations can be reconstructed with LISA, employing a method based on principal component analysis. We then perform a Fisher forecast for the parameters describing the oscillatory signal. For a sharp feature we distinguish between the contributions to the stochastic gravitational wave background induced during inflation and in the post-inflationary period, which peak at different frequencies. We find that for the latter case the amplitude of the oscillation is expected to be measurable with $< 10\%$ accuracy if the corresponding peak satisfies $h^2 \Omega_\textrm{GW} \gtrsim 10^{-12}$-$10^{-11}$, while for inflationary-era gravitational waves a detection of the oscillations requires a higher peak amplitude of $h^2 \Omega_\textrm{GW}$, as the oscillations only appear on the UV tail of the spectrum. For a resonant feature the detection prospects with LISA are maximised if the frequency of the oscillation falls into the range $\omega_\textrm{log} = 4$ to $10$. Our results confirm that oscillations in the frequency profile of the stochastic gravitational wave background are a worthwhile target for future detection efforts and offer a key for experimentally testing inflation at small scales.
Comment: 28 pages, 15 figures
Databáze: OpenAIRE